ObjectiveIt remains unclear whether Tai Chi is effective for preventing falls in older adults. We undertook this systematic review to evaluate the preventive effect of Tai Chi by updating the latest trial evidence.DesignSystematic review and meta-analysis.MethodsThe Cochrane Library, MEDLINE and EMBASE were searched up to February 2016 to identify randomised trials evaluating Tai Chi for preventing falls in older adults. We evaluated the risk of bias of included trials using the Cochrane Collaboration's tool. Results were combined using random effects meta-analysis.Outcome measuresNumber of fallers and rate of falls.Results18 trials with 3824 participants were included. The Tai Chi group was associated with significantly lower chance of falling at least once (risk ratio (RR) 0.80, 95% CI 0.72 to 0.88) and rate of falls (incidence rate ratio (IRR) 0.69, 95% CI 0.60 to 0.80) than the control group. Subgroup analyses suggested that the preventive effect was likely to increase with exercise frequency (number of fallers: p=0.001; rate of falls: p=0.007) and Yang style Tai Chi was likely to be more effective than Sun style Tai Chi (number of fallers: p=0.01; rate of falls: p=0.001). The results might be influenced by publication bias as the funnel plots showed asymmetry. Sensitivity analyses by sample size, risk of bias and comorbidity showed no major influence on the primary results.ConclusionsTai Chi is effective for preventing falls in older adults. The preventive effect is likely to increase with exercise frequency and Yang style Tai Chi seems to be more effective than Sun style Tai Chi.

Exosomes are vital mediators for intercellular communications in the tumor microenvironment to accelerate colon cancer progression. Leucine-rich repeat-containing 8A (LRRC8A), the core component of the volume-regulated anion channel, is closely associated with acquiring heterogeneity for tumor cells. However, the role of LRRC8A in the exosomes remains largely unknown. Here, we reported that LRRC8A was one of the compositions in the exosomes released from colon cancer HCT116 cells. Downregulation of LRRC8A proteins inhibited ex vivo cell growth and induced apoptosis. Consistently, chloride channel blockers DCPIB and NPPB inhibited cell growth and induced cell apoptosis in a time or concentration-dependent manner. Interestingly, the total amounts and proportions of different diameter exosomes released in 6 hours were not altered by the treatment of DCPIB and NPPB in HCT116 cells. In contrast to the downregulation or inhibition of LRRC8A, overexpression of LRRC8A proteins in HCT116 cells released significantly more distinct populations of exosomes. Importantly, the switches of ratios for exosomes in a hypotonic challenge were eliminated by DCPIB treatment. Collectively, our results uncovered that LRRC8A proteins were responsible for the exosome generation and sorted into exosomes for monitoring the volume regulation.

In order to improve the detection function of wearable intelligent devices in the Internet of things and facilitate people to control a variety of information such as heart rate, exercise state, blood oxygen saturation, and so on, the scientific detection of human physical health based on wearable devices based on Internet of things technology is proposed. Through the combination of software- and hardware-related functional modules, the real-time detection of human physical health information can be effectively realized. Firstly, the detection principle of optical capacitance product pulse wave signal and the waveform characteristics of pulse wave are introduced, and then the application scenarios and advantages of wearable devices are further introduced; then, the convolutional neural network for pulse wave signal denoising and the basic principle of self-encoder are introduced; finally, the regression prediction method and support vector machine method for pulse wave signal feature extraction are introduced in detail. The pulse wave based on optical capacitance product is removed to improve the waveform quality of pulse wave signal. Firstly, the system software development environment is briefly described. Then, the software design of watch terminal master device based on MSP432 and belt terminal slave device based on MSP430 are described in detail, and the detailed program implementation flow of each key technology in the system is given. In addition, the fall detection algorithm based on threshold discrimination is studied, and the program implementation of the algorithm is also described in detail. Finally, the system is tested. The results show that normal state mainly include normal walking, jogging, and fast sitting, and the accuracy rate is 97%, 95%, and 93%, respectively. For fall state, the experimenter needs to simulate various possible fall states, and the accuracy rate is 95%, 93%, and 95%, respectively, which verifies the detection accuracy of the algorithm. The system can automatically turn on the satellite positioning function when the user’s physical sign parameters are abnormal or the user’s current fall dangerous situation occurs, and send the current position information and alarm content information through the GSM module, so that the dangerous situation can be found and handled at the first time.

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